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As always, as soon as I release a library, I can see all the mistakes I was happy leaving in until other people could see it. In Group-By I found all sorts of inconsistencies in my approach, and so to make this tiny library better I rewrote the important bits. The main problem was that this started as an alist grouping mechanism. But alists became untenable at depths greater than 1 or 2, or if linear lookup was unacceptably slow. For more efficiency I had looked at grouping into hash table; for a usable interface I looked at grouping into CLOS tree-nodes. Then I combined all three approaches into a monstrosity. The problem with this approach was that it conflated wanting a nice/usable interface (which CLOS can provide), with the efficiency issues of looking up children via a hash table or list. As such I had this strange mirroring of awful to use datastructure backends, barely wrapped in a nicer CLOS interface.

No more, now the structure of multiple groupings is a CLOS tree of grouped-list objects, while the children are stored in a single hashtable or list on each tree node (with methods defined so you should never have to worry about the implementation other than to adjust performance). This greatly simplified my ability to think about what this library was doing, and cleaned up what I considered to be some fairly glaring ugliness. Overall i think this refactoring was a victory.

It would be nice to switch implementations from list to hashtable when we noticed the number of children increasing past a certain threshold, but I have left that for a later date.

A recurring problem I have experienced while programming, is the need to convert a flat list of data into a more complex tree data structure. This is especially common when dealing with results from relational databases (where all data is intrinsically flat, and queries return tables of data). To solve this problem I wrote a small library named group-by (in honor of the sql operator that performs much the same task).

The easiest example:

(group-by '((a 1 2) (a 3 4) (b 5 6)))
=> ((A (1 2) (3 4)) (B (5 6)))

A more concrete example is from trac, the ticketing system we use. Trac tickets contain fields for author, project, milestone, and summary (among others). When displaying this data, my project manager wants to be able to see what everybody is working on (a tree view organized by author, project, and milestone), as well as being able to see what is being worked on in a project and by whom (a tree view organized by project and milestone). To accomplish this I pull a flat list of ticket objects from the database (using a clsql-orm generated class). I then create a tree from this data table by calling make-grouped-list. I can then perform a standard recursive tree walk to render this with the desired organization directly.

Group-by supports grouping into alists, hashtables, and CLOS tree-nodes. To hide the difference between these implementations, I created a grouped-list CLOS object that manages all of the grouping and presents a unified interface to each of these implementation strategies. I support each of these implementations because which to use is strongly dependent on the workload you anticipate performing with the tree. Simply grouping once then recursively rendering the tree, is often more efficient as an alist, than a heavier weight data structure. Conversely, hashtables tend to perform better for lots of accesses into the grouping structure.

I just pushed cl-creditcard to my github account. CL-Creditcard( and sub-library cl-authorize-net) is a library that we use to process payments with Authorize.Net. We have a large internal application that tracks and manages all our business and customer logic including billing and invoicing. (Invoices are generated using cl-typesetting). This application charges credit card payments through this cl-authorize-net.

It has been stable and charging cards for years and I just got around to releasing it. Soon it will also support ACH (echeck) transactions and we will be moving to lisp-unit from lift.

As with all payment processing, test very well before putting into production :)

CLSQL-ORM is a common lisp library I just pushed to my git hub account. Its primary goal is to generate CLSQL-view-classes based on an existing database. It uses the “information_schema” views to introspect relevant data from the database, then builds and evals the view-class definitions. This project is a significant branch of clsql-pg-introspect, attempting to remove its “pg” aspects in favor of the standard “information_schema”. It might have changed some semantics/conventions along the way, (I’m not sure as I didn’t use the original project much, and that was long ago).

I wanted to generate my lisp objects from the database for a couple reasons. One, I am fairly comfortable with SQL databases and am used to specifying them in whatever variant of sql the database engine supports. Two, I am most often presented with an extant working database that I want to interact with (such as a wordpress install), where the schema of the database can change, and I just want my common lisp to match whatever the database says, rather than trying to keep both up to date with each other manually. Obviously this project encodes many of my own, personal thoughts and tastes about databases, which may not be the same as your thoughts and tastes. This project is perhaps best though of as a jumping off point for creating your own personal common lisp ORM, though it should be usable as is, if your tastes and mine coincide.

I just posted a small common lisp library to my github account named Symbol-Munger. Symbol-Munger provides functionality to ease conversion between the same symbol in different environments.

For example, when generating common lisp classes from a database schema, I want to change column names into lisp slot / accessor names, and then later when I am displaying that common lisp slot on the screen I want to display its slot-name as an english column header. (IE: my_db_col > my-db-col > My Db Col)

I have had this code laying about for years and use it everywhere frequently. Earlier today while cleaning other code, I ran across this TODO in vana-inflector, and realized I already had code that performed this function. This library contains one function that does the bulk of the work (normalize-capitalization-and-spacing) and many functions that set default arguments to that one (lisp->english, english->camel-case, english->keyword. etc). Its only dependency is iterate.

CSS-Selectors and TALCL are both, at heart, translators from some language (css-selectors and xml respectively) into compiled common lisp functions. We translate these expressions by translating the source language into a tree of common-lisp, inserting that common-lisp into a lambda form, then calling compile on that lambda. Because this is a central part of the utility they provide, slow compilation speed can be somewhat annoying. This led to me implementing compiler macros and other caching schemes so that compiling could be handled at compile time (when possible/constantp), where the slow compilation would be less problematic.

Below are the results comparing the two compilers. My experiment confirmed Xachs findings from 2007. The lambda tree version of the compiler is MUCH quicker (~1000x in SBCL) with comparable execution speed. This hasn’t sped up the (cl-yacc produced) parser, so I think that much of the caching and compiler macro code is still valid and still saving user time, just less crucially so now. The only downside I saw was that debugging was a touch harder because there was no human readable version of the fully translated expression (which I could get from the old translator).

Earlier this week I released a couple common lisp libraries. Thus for the rest of the week I have tried to make them usable by anyone who is not me. The situation is complicated by a few facts about our development environment. Our shared lisp library directory has been accreted over more than 5 years, and some of these libraries having been patched (some in darcs and some in git and most not patched upstream). We also make heavy use of precompiled cores to speed up start up time. All of this leads to an environment that is very hard to replicate. Quicklisp to the rescue! Quicklisp makes it easy to have a lisp environment with the same set of libraries available as everybody else, which is a tremendous win when compared to our difficult-to-replicate system.

To fix the bugs other people would see in the software that builds and works fine for me, I wrote an sbcl script to perform a clean build and fetch all unknown dependencies from quicklisp. (This script is not common lisp; there is sb-xxx all over the place.) I learned quite a bit about all of the related systems, so the end result seems somewhat trivial, but perhaps it will provide decent examples. Quicklisp is easy to install, and makes deploying usable common lisp libraries MUCH easier.

By running the following script I will load and test the buildnode system using only libraries pulled from quicklisp.~$ sbcl --script ~/run-builds.lisp --test-system buildnode --quicklisp-only

I have just pushed three Common Lisp libraries to my github account. We have been using Buildnode and TALCL internally for quite some time and CSS-Selectors was something of a learning project I just wrote.

Buildnode

Buildnode is a library to make working with CXML DOM documents and nodes easier. It smoothes some of the DOM interfaces to be a bit nicer and more in line with common lisp conventions. We use buildnode primarily to generate the output of webpages hooked up to our extensively modified UCW lisp web server. We also use it to generate excel spreadsheet XML and google earth KML. It facilitates writing small generation functions that can be built up and combined in any way. We also use it to generate “tag” packages which are a package of functions that build the XML tree for us (see the example).

Primary Features

Iterate drivers for the dom (in-dom-children, in-dom-parents, and in-dom)

DOM manipulation functions such as set-attribute, add-children etc that return the node they are manipulating to ease stringing many calls together and then appending the result to the dom

TAG Packages that make a library of functions for interacting with a specific XML dialect

TALCL

TALCL is a branch of ARNESI YACLML/UCW Template Attribute Language, which in turn was branch of Template Attribute Language originally developed in python for Zope. We think that this version of TAL is much improved over the one originally shipped with UCW by being simpler to use, has better integration with the lisp environment, and simpler evaluation rules. TALCL is divorced entirely from the UCW/ARNESI/YACLML stack and should be a usable choice for any templating need (though certainly specializing in XML templating). We use this library for HTML templates that our designers can work with as well as processing both plain text and HTML email templates in our internal billing software. Examples can be found in the repository.

CSS-Selectors

CSS-Selectors is a library that implements a parser for css-selectors level 3 and provides a compiler that can compile node-matcher functions from these selectors. It also provides a query function (much like jQuery), that can be used to retrieve a list of matching nodes from the dom. I use this for selecting dom nodes to manipulate from the output of an (unreleased) form controls library and for manipulating and pulling information from DOM documents. If static, compilation of CSS-selectors into node-matcher functions occurs at compile time.

I have been using Aqua Data Studio 7 since its release (and had used a couple versions before that I believe). I really enjoy using ADS, but have been wanting a new version for quite a while. Today while browsing their site I saw that a version 9 beta is available and also that they have a FREE license available for OSS developers. (They also offer student licensing). This is seriously quality software that makes my life so much easier. If you work with a variety of database systems, you can’t do much better than Aqua Data Studio to talk to all of them with one program.